Ecosphere

Diverse life history strategies allow species to spread risk across a mosaic of habitat conditions. In Chinook Salmon (Oncorhynchus tshawytscha), particularly in the Central Valley of California, this is expressed through varied adult run timings and juvenile outmigration strategies. Anthropogenic impacts, particularly dams, disrupt these fundamental life stage transitions, often forcing managed populations to adapt to homogenized, less stochastic hydrologic regimes. This is exemplified in the Sacramento River, where the conservation of endangered Sacramento River winter run Chinook salmon requires balancing complex water operations with the ecological needs of a population confined to a short stretch of suitable habitat downstream of Shasta Reservoir. Using a 23 year dataset (2002 to 2024), we evaluated the combined effects of flow, temperature, and spawner abundance on juvenile production and life history expression in this habitat. We found that flow and spawner abundance best predicted juvenile abundance at Red Bluff Diversion Dam while temperature had considerably less support. The proportion of juveniles migrating as smolts exhibited significant density dependence that was negatively correlated to both female spawner abundance and peak flows. These results suggest focusing on temperature management alone may be insufficient. Effective management strategies should consider flow variability and habitat restoration to facilitate varying migration strategies and expand upstream rearing capacity. By addressing these physical and hydrologic constraints, managers can better support the full suite of life history strategies necessary for the resilience of winter run Chinook salmon.

Streambank erosion degrades both terrestrial and aquatic ecosystems, and riparian buffers are among the most widely used tools to control it. Yet most of what is known about how riparian vegetation controls erosion comes from one or two-species systems, which overlook the diversity of riparian communities and species interactions (competition and facilitation) that may shape the root systems that bind soil. We used a streambank mesocosm experiment to test whether plant species richness alters root traits, and whether root traits and species interactions reduce erosion. We established 85 mesocosms ranging from unvegetated controls to six-species polycultures, measured root biomass, length, volume, and diameter, quantified species interactions with relative yield totals (RYT), and measured erosion rate with a jet erosion test. Vegetated mesocosms eroded significantly less than unvegetated controls (t = 4.05, p = 0.023). Richness did not affect most root traits, although mean root diameter decreased as richness increased ({beta} = -0.0225, p = 0.047). RYT ranged from competition (RYT < 1) to facilitation (RYT >1), yet neither interactions nor any root trait was directly associated with erosion rate. However, RYT was negatively associated with soil moisture ({beta} = -0.196, p = 0.010). Piecewise structural equation models showed that erosion was best explained by a pathway linking species presence, root length, and soil moisture (AIC = 39.27; Fisher's C = 11.27, df = 12, p = 0.506). Panicum virgatum increased root length, whereas Lolium multiflorum and Echinochloa crus-galli reduced it; longer roots were associated with drier soil (standardized {beta} = -0.31, p = 0.005), and wetter soils eroded more slowly (standardized {beta} = -0.39, p < 0.001). Which species were present mattered more than how many, and plants were linked to erosion through soil moisture rather than root traits alone. Species selection for riparian buffers may need to consider effects on soil moisture as well as rooting extent, particularly as droughts followed by intense storms become more common under a changing climate.

Researcher disturbance can alter the behavior, survival, and breeding success of wildlife, with effects that are especially well-documented in waterbirds. Anecdotal reports suggest that disturbance can even cause cavity-nesting species to alter the structure of their nests. We used a long-term study of a burrowing seabird, the Leach's Storm-Petrel (Hydrobates leucorhous), to ask whether storm-petrels renovate existing burrows and whether such renovation is related to a history of researcher disturbance. Our study was conducted at the Bowdoin Scientific Station on Kent Island, New Brunswick, Canada, where in 2024 we measured the burrow architecture of 363 burrows, including length and structure for occupied and unoccupied burrows both inside and outside a long-term study site with consistent research activity. Of these, 150 burrows had been measured in 2006, allowing for direct longitudinal comparison of burrow architecture. Nearly all burrows changed in length over the 18-year study period (mean absolute change = 20.8 cm +- 18.2 SD). A linear model revealed two contrasting processes of burrow length change: more frequently occupied burrows grew longer, whereas initially longer burrows shortened towards mean burrow length (~50 cm) through collapse. Occupied burrows inside the long-term study site were on average 34% longer and significantly more complex than burrows adjacent to the site, suggesting that researcher disturbance directly or indirectly reshapes burrows. Overall, these results show that storm-petrel burrows are shaped by cycles of renovation and subsequent collapse that may be exacerbated by human disturbance. Given ongoing population declines in storm-petrels and other cavity-nesting seabirds, this study emphasizes the need to balance scientific research with minimizing disturbance, particularly in long-term studies.

Introduction: Despite decades of investment, stream restoration often fails to recover diverse benthic macroinvertebrate communities, as restored reaches tend to remain dominated by pollution-tolerant taxa. This shortfall in recovery is commonly attributed to either poor habitat quality or dispersal limitation of aquatic macroinvertebrate taxa, yet these hypotheses are rarely tested directly. Objectives: We conducted a manipulative field experiment in the eastern Piedmont region (Maryland, USA) within the Chesapeake Bay Watershed to evaluate whether restored streams can support pollution-sensitive taxa when dispersal barriers are removed. Methods: We translocated whole macroinvertebrate communities from three nearby reference streams into three restored streams using standardized habitat substrates and quantified macroinvertebrate survival after 28 days. We also assessed how effective leaf vs rock substrates were for accumulating diverse and abundant macroinvertebrate communities for translocation. Results: Across all sites, 77% of translocated individuals and 16 of 22 taxa sensitive and moderately sensitive to pollution persisted under restored stream conditions, demonstrating that restored reaches can support short-term survival of pollution-sensitive taxa that typically fail to recover. Substrate comparisons revealed that leaf packs accumulated higher macroinvertebrate abundances, whereas both substrates accumulated macroinvertebrate communities with similar taxa richness, EPT richness, and Shannon Diversity. Conclusions: This work suggests that dispersal limitation, rather than unsuitable habitat, may be an underappreciated constraint limiting macroinvertebrate recovery in restored streams. These findings challenge the assumption that habitat restoration alone is sufficient for biological recovery and highlight the potential for whole-community translocations to accelerate recovery and ecological uplift as part of stream restoration practices. Implication for Practice: Our study highlights the need to consider habitat connectivity and dispersal pathways during stream restoration designs. Restoring streams to meet habitat requirements of pollution-sensitive macroinvertebrate taxa may not be sufficient for their populations to recover if these taxa are unable to reach the restored stream. In scenarios where restoring connectivity to source populations is infeasible, whole community translocations may offer a novel restoration tool to overcome dispersal barriers and accelerate biological recovery in restored streams.

Okanagan sockeye salmon have shown a strong recovery over the past three decades, but the contribution of environmental conditions and management actions to this recovery has not been determined. We developed a hierarchical Bayesian model linking spawner abundances to fry emergence observations to evaluate how flow and water temperature during adult upstream migration and incubation periods influence spawner-to-fry production. Production declined by 62% in years with earlier onset and longer duration of periods when warm river temperatures created barriers to adult migration, indicating that migration conditions can have carry-over effects on reproductive success even when spawners successfully reach the spawning grounds. Additionally, production was 46% lower when flows fell above or below the management target range designed to minimize scour and desiccation during egg incubation. In contrast, we found little support for effects of pre-spawning flows or incubation temperature on production. These findings provide quantitative evidence that current flow management is increasing freshwater spawner-to-fry production and has likely contributed to the Okanagan sockeye recovery. Effective flow management may therefore help offset climate-driven impacts that increasingly threaten this population.

Riverine and riparian food webs are connected via 'allochthonous' resource flows from neighboring ecosystems. These resources, such as terrestrial leaf litter, contribute to benthic macroinvertebrate diets, supporting higher trophic levels. While allochthony occurs in streams globally, its sensitivity to broad environmental gradients remains poorly understood. We explored the drivers of allochthony across six river basins within the contiguous United States, including climate, stream size, and flow permanence. We used Bayesian mixing models to estimate macroinvertebrate dietary proportions in four functional feeding groups. Air temperature best predicted allochthony, with consumers relying less on allochthonous resources with increasing temperature. Our models indicate that macroinvertebrate diets become primarily autochthonous at approximately 15{degrees}C mean annual air temperature, with leaf litter-consuming shredders showing a slightly higher threshold for this shift. We also found increased allochthony in smaller, non-perennial streams. These findings highlight the complexity of stream allochthony and responses to multi-scale environmental factors.

Fishery-dependent indices of abundance are often used to inform stock assessments, but fishing effort is generally not randomly distributed. Fishers concentrate sampling in locations expected to be profitable, leading to a form of preferential sampling that can bias model-based indices of abundance. We show that when the strength of preferential sampling is constant over time, it biases only the magnitude of an index, which is absorbed by estimated catchability parameters in most stock assessments. A more interesting case arises when the strength of preferential sampling changes over time; in these cases the index trend can be biased in a way that conventional catchability estimation cannot correct. Using simulations structured on long running trawl survey data from the west coast of the USA for shortspine thornyhead (Sebastolobus alascanus), we evaluate two structurally different methods for correcting time-varying trend bias: a joint spatiotemporal model of the density and sampling processes, and a discrete-choice model of fisher location choice. Our simulations include two mechanisms generating preferential biases: effort tracking local density, and effort responding to a spatially structured, but unobserved anomaly that also inflates catch. We show that the ability of the estimation methods to correct bias depends on the mechanism responsible for concentrating effort; while the joint model is robust to both data-generating mechanisms, the discrete choice model is only able to correct biases when the mechanism is anomaly-driven. As a real-world case study, we apply these corrections to simulated preferentially sampled data and include indices in the shortspine thornyhead stock assessment model. We found that uncorrected time-varying preferential sampling positively biased estimates of a major recruitment event and, to a lesser extent, unfished recruitment. This bias propagated through to bias in overfishing limits that grew as the population was projected forward. While bias-corrected indices still produced some positive biases in overfishing limits, these were substantially reduced compared to the naive approach. As the mechanism of preferential sampling is rarely known in advance, our results suggest that the joint model represents a robust default for correcting fishery-dependent indices of abundance.

Animal movements can transport materials across ecosystem boundaries, while simultaneously modifying habitats through physical engineering. We integrated GPS telemetry, camera trapping, sediment measurements and physicochemical sampling of ponds on Santa Cruz Island, Galapagos, to evaluate how giant tortoises connect and shape terrestrial and freshwater ecosystems. Telemetry revealed 2,254 visits by 21 tortoises to 12 ponds, with visits lasting up to 21.38 h and showing strong seasonal and diel variation, while camera traps showed peak pond use in January and during early morning and late afternoon. Greater tortoise abundance was associated with higher ammonium, dissolved organic carbon and total phosphorus concentrations, while ponds with persistently greater tortoise abundance had higher total suspended solids. Departing tortoises carried a mean 505.9 g of sediment, yielding a conservative potential export of 8.20 kg per tortoise per year and tens of tonnes annually. These findings identify giant tortoises as mobile zoogeochemical engineers linking terrestrial and freshwater ecosystems through physical and biogeochemical pathways.

Stemflow transports water and biological material from forest canopies to the stem base, yet fungal studies of this flux have largely relied on microscopy of conidia. We used ITS2 metabarcoding to characterize fungal environmental DNA (eDNA) in stemflow from 15 trees - five each of American beech (Fagus grandifolia), sugar maple (Acer saccharum), and tulip poplar (Liriodendron tulipifera) in a closed-canopy forest in northeastern Ohio, USA. Stemflow was sampled during eight rain events in the leafless season (November 2024-May 2025), along with simulated bark and gutter washes to assess near-collar and collector signals. Natural stemflow communities were compositionally distinct from both controls and occupied greater ordination space. Ascomycota dominated across all samples, with Parafenestella, Cytospora, Microcera, Nectria, and Aureobasidium among the most abundant resolved genera and 13 of the 25 most abundant taxa differed significantly among host species. Woody-plant-associated endophytes, canker fungi, and saprobes dominated ecological guild composition. Storm event explained 28.6% of taxonomic variation, host tree species 24.1%, and their interaction 10.0%. Guild composition was more strongly structured by host species (35.4%) than storm event (20.4%). Lichenized fungi and lichen-associated fungi were detected. Thus, leafless-season stemflow integrates broad bark-associated fungal eDNA, including recurrent lichen-derived material, beyond the morphologically distinctive conidia captured by traditional methods. Stemflow eDNA therefore offers a minimally invasive means of monitoring canopy fungal diversity and the strong host and temporal filtering of DNA exported from woody surfaces.

Freshwater biodiversity is declining at alarming rates globally, yet our capacity to monitor it depends heavily on the methods used for biodiversity assessment. Stream benthic macroinvertebrates are widely used as bioindicators, but traditional morphological identification is labor-intensive and limited by taxonomic expertise, while DNA metabarcoding offers a promising but incompletely evaluated alternative. Here, we compared biodiversity patterns detected by four macroinvertebrate sampling and identification methods (morphological identification of benthic samples, morphological identification of combined benthic and stream-edge samples, eDNA metabarcoding of bulk benthic samples, and eDNA metabarcoding of streamwater) across 62 sites in seven watersheds spanning the southern continental United States. We compared methods across three facets of biodiversity (gamma diversity, alpha diversity, and taxonomic composition) and three taxonomic levels (family, genus, and species). We found that which method detected more taxa shifted with taxonomic resolution: morphological methods detected more families and genera, while metabarcoding methods detected more species. Bulk benthic metabarcoding detected more families and genera than water eDNA metabarcoding, consistent with the "watered-down biodiversity" effect of DNA dilution in water samples, but the two metabarcoding methods did not differ significantly in species richness. All four methods detected largely distinct suites of taxa, with metabarcoding methods yielding more unique taxa than morphological methods. Notably, taxa uniquely detected by water eDNA were dominated by soft-bodied organisms (oligochaetes, leeches, earthworms) and water-column-associated taxa, while benthic eDNA uniquely detected hard-bodied EPT insects. We attribute this pattern to fundamental differences in eDNA shedding, transport, and deposition dynamics across organism types. These results demonstrate that no single method captures a complete picture of stream macroinvertebrate biodiversity, and that method choice should be guided by the taxonomic resolution and community components most relevant to the goals of the bioassessment program.

Arboreal camera trapping is an emerging remote sensing tool for building plant-frugivore interaction networks with enormous potential to provide new insights into seed dispersal as an eco-evolutionary process. Interaction data derived from camera trap videos broadly falls into two categories: visitation, indicating the presence of an animal in a tree, and intake, indicating true fruit consumption. These linked approximations of seed dispersal may or may not provide distinct sets of information, shaping our understanding of network dynamics, yet the extent to which emergent network structure depends on variable choice is unknown. To address this gap, we deployed camera traps in the canopy of 21 plant species in the Costa Rican tropical dry forest, an endangered biome with sparse community-wide plant-frugivore interaction data. Our objectives were: 1) Quantify plant-frugivore network structure in the tropical dry forest via network, group, and species-level metrics; and 2) Compare metrics between visitation and intake networks. We find strong structural patterns of low connectance, low nestedness, high modularity, and low niche overlap that differ significantly from null expectations in the same direction in both networks. The visitation network exhibited significantly greater modularity & species degree than the intake network, while the intake network exhibited significantly greater plant niche overlap than the visitation network. These findings suggest that the likelihood of consuming fruit on camera differs across species, which may have downstream consequences on other emerging metric estimations. Researchers seeking to build quantitative plant-frugivore networks should therefore consider visitation and intake variables in concert when relying on camera trap data. This work provides foundational plant-frugivore interaction data for a critically endangered biome and enhances our understanding of camera trapping as a remote sensing tool in frugivory and seed dispersal research.

1. Soil invertebrate biomass is closely linked to ecosystem processes, yet its routine quantification remains constrained by the effort required to weigh large numbers of small individuals. Length-mass relationships provide an indirect alternative, but body length can be difficult to standardise and extract automatically from images of curved, coiled or contracted organisms. Projected body area may provide a more tractable image-derived predictor, but its performance across diverse soil-faunal taxa and at the community scale remains insufficiently evaluated. 2. Here, we developed a framework using projected body area and contour length to estimate fresh and dry mass from measurements of 1,792 soil invertebrates representing 15 higher-level taxa. We fitted taxon-specific models for six well-represented groups and general models across taxa, and evaluated predictive performance using leave-one-out cross-validation. We then assessed cross-dataset transferability by comparing our data with those of Lemoine et al. (2026) and pooled the two datasets to derive combined models. Finally, we tested whether individual predictions could be scaled to independently measured community biomass. 3. Taxon-specific models generally reduced prediction error relative to general models, with mean absolute percentage error (MAPE) values of 6.9-37.3% for fresh mass and 7.6-30.2% for dry mass. General models retained MAPEs of 27.2% and 22.4%, respectively. Comparisons of our dataset with that of Lemoine et al. (2026) showed no detectable differences in six of eight taxon-by-mass slopes. Although intercepts frequently differed, no overall dataset effect was detected after accounting for taxa. Pooling both datasets broadened model development, while taxon-specific models generally retained lower error than the combined general model. Finally, community-level predictions tracked measured biomass across all model sets (R2 = 0.87-0.99), but absolute error varied among models and faunal groups (MAPE = 9.6-52.5%). 4. Body area and contour length extracted from images therefore provide a practical basis for scaling soil invertebrate biomass estimation from individuals to communities. Integration with automated imaging and segmentation tools such as flatbug, BIODISCOVER and CollembolAI could extend soil invertebrate monitoring at larger scales beyond abundance and taxonomic composition to biomass, while providing scalable inputs for analyses of food webs and general ecosystem ecology.

Subsurface tile drainage rapidly transports nutrients and biological contaminants to surface waters, yet multi-year evaluations of drainage water management (DWM) effects on nutrients, Escherichia coli, and antibiotic resistance genes (ARGs) remain limited. A paired-field design with high-frequency soil moisture monitoring was used to quantify water yield, dissolved nitrogen, phosphorus, and Escherichia coli (E. coli) over seven and eight water years, and ARGs (tetM, tetW, ermB, sul1) over two years in southern Michigan. Soil moisture at tile depth (~75 cm) was higher under controlled drainage, confirming that DWM increases field water-holding capacity. Compared to the free drainage field, DWM reduced cumulative tile discharge by 43% and annual nutrient yields by 46-83% for nitrate and 12-82% for soluble reactive phosphorus, but effects on ammonium were variable. Average daily nutrient yields declined by ~50% over the study period, driven primarily by managed periods. Nutrient concentrations did not differ between treatments, indicating that yield reductions resulted from decreased water loss. Mean daily E. coli yields declined by 71% over the study period, and concentrations were 46% lower under controlled drainage. Controlled drainage reduced tetM and sul1 ARG concentrations and yields during managed periods and throughout the study; however, sensitivity analyses showed that these effects were strongly influenced by a high-precipitation event. After excluding the event, differences in ARG concentrations were no longer detected, although ARG yields remained 43% lower during managed periods. These findings highlight the potential for DWM to mitigate nutrient, microbial, and antibiotic resistance transport from agricultural drainage systems.

Forest canopy height is sensitive to shifts in demography (which affect tree size distributions and abundances of short-vs. tall-statured species) and allometry. Demographic and allometric effects on canopy height have not previously been studied across a large region. We analyzed more than two million individual tree measurements from about 60,000 remeasured inventory plots in non-plantation forests across 19 ecoregions of the conterminous United States to quantify changes in aboveground live tree biomass (AGB), canopy height, and its demographic and allometric components from ~2003-2025. We tested the hydraulic limitation hypothesis, which predicts decreasing tree height with increasing hydraulic stress. AGB was strongly correlated with canopy height across ecoregions, and AGB change was strongly correlated with canopy height change over time. Canopy height change was positive in nearly all eastern ecoregions but varied in sign across western ecoregions. Demographic shifts led to increased canopy height in most eastern ecoregions but decreased canopy height in most western ecoregions. In contrast, allometric shifts, averaged across species, caused either positive or no significant change in ecoregion-mean canopy height. Our results were consistent with several predictions of the hydraulic limitation hypothesis: (i) intraspecific allometric shifts were more positive for understory than for canopy trees, (ii) across ecoregions, canopy height was positively correlated with precipitation and negatively correlated with vapor pressure deficit, and (iii) canopy height change over time was positively correlated with precipitation change. However, our results suggest modifications to the hydraulic limitation hypothesis, because allometric shifts tended to be positive, even in ecoregions with decreasing precipitation and increasing vapor pressure deficits. Such allometric shifts, which seem counter to the hydraulic limitation hypothesis, may be caused by CO2-driven increases in water-use efficiency. Whatever their cause, allometric shifts should be accounted for to avoid biased estimates of canopy height change and biomass change.

Reforestation is a leading natural climate solution, but bulk soil organic carbon (C) often responds slowly, obscuring early belowground change. We tested whether soil aggregates reveal early structural reorganization that affects C retention pathways at a three-year-old experimental reforestation planting established on former pasture in Oregon, USA. We sampled soils at 0-20 and 20-40 cm beneath incense cedar (Calocedrus decurrens; arbuscular mycorrhizal [AM]), black cottonwood (Populus trichocarpa; AM and ectomycorrhizal [EcM]), ponderosa pine (Pinus ponderosa; EcM), and treeless controls. We measured bulk soil C concentration and C:N, aggregate size distribution and mean weight diameter (MWD), fraction-associated C, and, in a subset of surface aggregate fractions, natural-abundance {delta}13C to evaluate soil C pools, physical structure, C distribution, and C processing. After three years, reforestation did not produce significant differences in bulk soil C between planted trees and treeless controls. In surface soil, MWD averaged 36% higher under incense cedar and 58% higher under black cottonwood than under controls, whereas ponderosa pine remained similar to controls. The clearest treatment differences in C distribution occurred in macroaggregates. Incense cedar and black cottonwood had higher large (>2000 m) macroaggregate-associated C than controls, while black cottonwood combined a greater proportion of large macroaggregates with lower C concentrations, indicating that structural development and C accumulation were partly decoupled. Species patterns were broadly consistent with stronger early aggregate responses under AM-compatible species in former-pasture legacy conditions; by contrast, the EcM-associated ponderosa pine remained closer to treeless controls across multiple aggregate measures. Treatment effects weakened with depth and were limited in microaggregates (250-53 m) and silt-and-clay (<53 m) fractions. Smaller aggregate fractions were progressively enriched in {delta}13C, consistent with greater C processing in protected fractions, but treatment-level isotope differences had not yet emerged. Soil aggregates showed species-associated belowground reorganization, revealing how tree identity and former-pasture legacy may shape early soil C organization before consistent differences emerged in bulk soil C. Aggregate measures can complement bulk soil C measurements in restoration monitoring as early indicators of belowground soil C trajectories shaped by tree species identity and land-use legacy.

1. Detecting causal relationships from ecological time series remains challenging because community dynamics are often nonlinear, high-dimensional, noisy, and strongly synchronized. These characteristics can reduce the reliability of existing causal inference methods and complicate the identification of ecological interactions in complex natural systems. 2. I introduce Forest-weighted Causal Correlation (FORCC), a machine-learning-based framework that infers directional causality from adaptive neighborhood structures learned by random forests. Rather than evaluating causal direction through cross-map reconstruction, FORCC quantifies directional dependence from the preservation of neighborhood structure using rank-based associations among forest-weight matrices. 3. Simulations of coupled nonlinear systems showed that FORCC accurately recovered causal direction while substantially reducing synchronization-induced false-positive detections relative to conventional convergent cross mapping. Chatterjee's {xi} exhibited the strongest resistance to synchronization-induced errors among the evaluated rank-based statistics. 4. Application to a 12-year marine community time series from Maizuru Bay, Japan, identified asymmetric relationships between individual taxa and community dynamics, revealing candidate driver-like and passenger-like roles that were not readily explained by seasonal synchrony alone. 5. By combining adaptive neighborhood learning with rank-based causal inference, FORCC provides a scalable framework for causal discovery in ecological time series. The method offers a practical tool for screening causal relationships, generating ecological hypotheses, and investigating complex interactions in multivariate natural systems.

Boreal forested streams receive substantial inputs of terrestrial carbon (C) from riparian vegetation in the form of leaf litter, which is processed by litter-associated microorganisms. In addition to these leaf-litter C inputs, boreal streams also receive significant concentrations of dissolved organic carbon (DOC), which may represent an alternative major resource pool for litter-associated microorganisms. As leaf litter quality decreases over the process of decomposition, DOC may increasingly become a more suitable C source for the microbial communities. We investigated how DOC availability, litter type, and microbial succession influenced respiration and decomposition. Alder, birch, and spruce litter were incubated for 65 days in 12 outdoor experimental channels supplied with natural boreal stream water. Higher time-adjusted DOC concentrations were associated with higher respiration and lower relative mass remaining, whereas DOC flux received less support. Respiration and mass loss followed litter-specific trajectories, with birch showing a respiration peak that was not matched by proportional mass loss. Prokaryotic and eukaryotic communities differed among litter types and changed through time but explained process variation only for specific litter types and responses. Our results suggest that DOC can sustain litter-associated microbial activity and partly decouple respiration from litter decomposition, thereby affecting boreal stream C processing.

Exotic species can reshape native communities, in the extreme, to local extirpation. Before that, natives may adjust where and when they use the landscape, in ways that allow coexistence and may be the earliest sign of trouble. Distinguishing coexistence built on such adjustment from one built on pre-existing niche differences requires comparing a native where the invader is absent with the same native where it is present, across sites at different invasion stages. Using eight years (2018-2026) of camera-trap data from 103 stations across Uruguay (154,590 camera-nights), we asked how the invasive axis deer (Axis axis) affects the space and time use of two native cervids: the forest-dwelling brown brocket (Subulo gouazoubira) and the grassland-restricted pampas deer (Ozotoceros bezoarticus). Activity-overlap, directional-avoidance, hierarchical activity, and two-species occupancy analyses showed sharply divergent dyads. A. axis and S. gouazoubira shared forest yet segregated in space and along the understory stratum the brocket requires and the invader avoids, and shifted their diel activity by context; understory cover fell with A. axis abundance, consistent with habitat modification. For A. axis and O. bezoarticus, segregation was intrinsic, opposite diel niches and habitats, with no support for a detectable shift in pampas deer behavior. The only behavioral signal was asymmetric: the invader, rather than the native, appeared to adjust, though few shared sites warrant caution. The same invader thus drives different mechanisms, but coexistence is provisional: A. axis is still expanding, far from equilibrium, so these shifts read best as early warning signals.

Management of marine protected areas (MPAs) require long-term monitoring and evaluation that is often limited by the cost and effort of conventional visual based surveys. We evaluated a community science-based eDNA approach to MPA monitoring over two years in the Point Dume State Marine Reserve, the Point Dume State Marine Conservation Area, and two paired unprotected reference sites. Across the sampling period, we detected 119 species of fish and marine mammals, including 19 of the 22 regional management-priority species for Southern CA MPAs. Protected and unprotected comparison sites were broadly similar in overall assemblage with 93 species shared across all sites. Multivariate analyses revealed site-level differences, although season and year explained more variation than protection status. Species presence also shifted during a La-Nina transition, highlighting the importance of long-term monitoring under different climatological contexts. Community scientists greatly expanded the temporal and spatial scope of eDNA sampling and generated high-quality data. Subsampling analysis showed that quarterly sampling, with three sample replicates and sequencing depths between 700k-990k, recovered 95% of observed biodiversity of the full time series. These results demonstrate that a community science-based eDNA program could provide a standardized, scalable, low-cost, and management-relevant approach for long-term monitoring across California's MPA network.

Recent work on the design of spatial capture-recapture (SCR) studies has largely focused on settings with a single set of movement and detection parameters. In many applied contexts, however, populations are naturally stratified-for example, when different sexes exhibit markedly different movement scales and encounter processes, or when more than one focal species is monitored. Designs that perform well for one group may be inefficient or suboptimal for others, despite the substantial logistical effort typically required to implement an SCR survey. We describe several potential SCR design strategies for surveying multiple groups, and compare these using simulation. Designs considered include regular and optimised grids, clustered and lacework designs, and designs generated using genetic algorithms, including new approaches that optimise information from both groups and a recently published two-stage design. Using proximity detectors such as camera traps, we evaluate design performance in terms of precision, bias, and coverage, and examine how performance changes with the number of available resources. Our results show that multi-group SCR surveys can perform well even when focal groups differ greatly in movement scale and encounter rate, provided that some simple guidelines are followed. Systematic layouts accommodating more than one characteristic spacing e.g. cluster designs, performed consistently well and are a reliable default option. Regular grid designs with a single spacing between detectors are feasible when differences between groups are moderate but performed poorly as differences increased. Establishing when these designs become problematic adds unnecessary risk to the design process. Algorithmic designs did not outperform systematic designs even in highly-skewed scenarios expected to favour them. In practice, when there is more than one focal group we recommend identifying the smallest and largest plausible movement scales and rejecting potentially pathological designs, primarily those that cannot generate recaptures at the smaller scale or cover a substantial area at the larger scale.